Bioinformatics: A One Semester Course
Sayood, Khalid, Otu, Hasan H.
- 出版商: Springer
- 出版日期: 2024-02-09
- 售價: $2,780
- 貴賓價: 9.5 折 $2,641
- 語言: 英文
- 頁數: 128
- 裝訂: Quality Paper - also called trade paper
- ISBN: 3031200195
- ISBN-13: 9783031200199
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相關分類:
生物資訊 Bioinformatics
海外代購書籍(需單獨結帳)
相關主題
商品描述
This book focuses on bioinformatics, the study of the management and analysis of information used in biological systems. Particular emphasis explains to the reader how to study and extract useful information, such as relatedness of species, function of specific sequences, and genome organization from genomic sequences.
This book focuses on the algorithmic aspects of bioinformatics and not on databases and software packages. There are two important discriminating characteristics that sets the book apart. It connects the algorithmic aspects and approaches to bioinformatics with the biological context while maintaining a user friendly and accessible description of the algorithms. The authors have curated the content for use a stand alone reference or the book will fit a one semester course on the subject.
作者簡介
Hasan H. Otu obtained his B.S. degree in 1996 and his M.S. degree in 1997, both from Bogazici University, Department of Electrical and Electronics Engineering. In 2002, he graduated from the University of Nebraska-Lincoln with a Ph.D. in Electrical Engineering focusing on Bioinformatics. He has been a faculty member at Harvard Medical School (2003 - 2012), where he was a research fellow between 2002-2003. He is the founding director of the Bioinformatics Core at Beth Israel Deaconess Medical Center, Harvard Medical School and Associate Director of the Proteomics Core at Dana Farber Harvard Cancer Center. Between 2010-2013, he acted as the founding chair of the Department of Genetics and Bioengineering at Istanbul Bilgi University. Since 2013, he has been serving as Professor of Electrical and Computer Engineering at the University of Nebraska-Lincoln. His research interests are in Bioinformatics, focusing on macromolecular sequence analysis, microarrays, biomarker discovery, genetic variations, systems biology, and analysis of high throughput biological data within the context of networks.